Estimate of Turbulent Energy Dissipation Rate From the VHF Radar and Radiosonde Observations in the Antarctic

Kohma, Masashi; Sato, K.; Tomikawa, Yoshihiro; Nishimura, Koji; Sato, Toru

doi:10.1029/2018jd029521

Cited by 34 publications

(47 citation statements)

References 99 publications

(160 reference statements)

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“…The strongest turbulence below the tropopause is also seen from individual profiles as well, which will be demonstrated in Figure 11a. The height of the maximum ε in the current study is different from some previous studies using radar data (e.g., Nastrom & Eaton, 1997, 2005 and the recently published results of Kohma et al (2019), which showed the maximum ε occurring just above tropopause primarily by the changes in the static stability (N) under nearly height-independent TKE around the tropopause. This is different from the current study of which the vertical profile of ε is determined primarily by L T that is generally larger where N is smaller, as will be shown in Figures 7b and 7c.…”

Section: 1029/2019jd030287contrasting

confidence: 99%

“…Several studies have compared the turbulence estimated from the Thorpe analysis with the turbulence derived from other methods. There have been studies comparing turbulence from radiosondes with turbulence from radar (Hoshino et al, 2016;Kantha & Hocking, 2011;Kohma et al, 2019;Li et al, 2016;Luce et al, 2014;Wilson et al, 2014). Schneider et al (2015) calculated turbulence from radiosondes and from an instrument called the Leibniz Institute of Turbulence Observations in the Stratosphere (LITOS), which had an 8-kHz sampling frequency and compared the two turbulence distributions.…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of Atmospheric Turbulence Retrieved From High Vertical‐Resolution Radiosonde Data in the United States

Chun

Wilson

et al. 2019

JGR Atmospheres

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In this study, we estimate atmospheric turbulence in the free atmosphere in terms of the Thorpe scale (LT) and eddy dissipation rate (ε) using U.S. high vertical‐resolution radiosonde data over 4 years (September 2012 to August 2016) at 68 operational stations. In addition, same calculations are conducted for 12 years (October 2005 to September 2017) at four stations among the 68 stations. These high vertical‐resolution radiosonde data have a vertical resolution of approximately 5 m and extend to an altitude of approximately 33 km, and thus, turbulence can be retrieved in the entire troposphere and lower stratosphere. There are thicker and stronger turbulent layers in the troposphere than in the stratosphere, with mean ε values of 1.84 × 10−4 and 1.37 × 10−4 m2/s3 in the troposphere and stratosphere, respectively. The vertical structure of ε exhibits strong seasonal variations, especially in the upper troposphere and lower stratosphere, with the largest ε values in summer and the smallest in winter. In the horizontal distribution of ε, large ε is seen mainly above the mountainous region in the troposphere, but this pattern is not seen in the stratosphere. Although ε is estimated by the square of LT multiplied by the cube of the Brunt‐Väisälä frequency (N), the regions of large ε are matched with large LT regions where N is relatively small. For the time series of ε near the tropopause for 12 years at four stations, an annual variation is prominent at all stations without significant interannual variations. There is, however, a slightly increasing trend of ε at two stations.

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Section: 1029/2019jd030287contrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characteristics of Atmospheric Turbulence Retrieved From High Vertical‐Resolution Radiosonde Data in the United States

Chun

Wilson

et al. 2019

JGR Atmospheres

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“…Considering that the direct solar point is passing through the tropical western Pacific from north to south at this time, a significant increase in turbulence activity may occur from July to September. Kohma et al [26] mentioned that seasonal variation in radar-based ε shows a broad maximum in August-October and low values in November-January in the lower stratosphere, which is similar to our results. The statistical characteristics of gravity waves at Gadank, which has the same latitude as Guam, are discussed in detail in [53][54][55], which have a certain reference significance for the turbulence distribution characteristics in this paper.…”

Section: Overview and Discussionsupporting

confidence: 93%

“…Nath et al used high-resolution GPS radio measurements over Gazanki in the tropics for nearly three years to investigate the characteristics of the seasonal variation and height distribution of various turbulence parameters [23]. Kohma et al estimated ε in the Antarctic region for a whole year and compared the results of radar data by using the Thorpe method [26]. Jian Zhang et al used high-resolution radiosonde data from 2012 to 2016 in mid-latitude regions to validate the credibility of Thorpe analysis in atmospheric turbulence studies [27].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Turbulence Characteristics over the Tropical Western Pacific Based on Radiosonde Data

Sheng

Zhou

et al. 2020

Atmosphere

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The tropical region is a key area for the interaction between the stratosphere and troposphere. The strong convective activity in the troposphere produces a series of gravity wave activities, which result in strong and widespread turbulence over the region. Therefore, studying the turbulent activity in the western Pacific is essential for understanding the characteristics of atmospheric disturbance over this region, which has the world’s most complex circulation system. In this paper, we explore the characteristics of atmospheric turbulence distribution over Guam in this region, and the Thorpe sorting method is used to study one-second resolution radiosonde data from the US. On the basis of the background field and local instability, the turbulence generation mechanism is discussed in detail. Results show that the US high-resolution balloon data are efficacious for tropospheric turbulence retrieval but increasingly affected by instrument noise as altitude increases. It is also found that there is a strong turbulent mixing band caused by both shear instability and static instability near the tropopause, where the turbulence activity is markedly enhanced and characterized by annual oscillation, reaching the maximum from July to September.

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“…Hence, high degree of intermittency and spatial variability of turbulence occurring in the free atmosphere cannot be accounted by the single radiosonde profile. Other than this, the proportionality constant between Thorpe scale and Ozmidov scale, that is, c = L o /L T varies with altitude with values ranging from 0.3 to 1 at different altitudes (Kohma et al, 2019).…”

Section: Statistical Comparison Of Turbulence Parameters From Both Tementioning

confidence: 99%

Estimation of Turbulence Parameters Using ARIES ST Radar and GPS Radiosonde Measurements: First Results From the Central Himalayan Region

et al. 2020

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Turbulence in the atmosphere plays a vital role in controlling the surface, lower and upper tropospheric dynamics. Here, we have utilized a newly installed Aryabhatta Research Institute of Observational Sciences (ARIES) Stratosphere Troposphere (ST) radar at the high‐altitude subtropical site in the central Himalayan region (Nainital, 29.4°N, 79.5°E, 1793 m above mean sea level) for the first ever estimation of turbulence parameters from this unique location. We have used radar observations made in years 2017 and 2019 with simultaneous and colocated global positioning system (GPS) radiosonde observations. In this context, turbulence parameters like turbulent kinetic energy dissipation rate, and eddy diffusion coefficient due to thermal and momentum fluctuations, have been determined by using (i) wind variance, (ii) Doppler spectral width, and (iii) backscatter signal power methods as well as synergistic radiosonde measurements using Thorpe length scale method. The kinetic energy dissipation rate and eddy diffusivity coefficients were found to be as high as 10−2 m2/s3 and 102.6 m2/s, respectively. Statistical distribution of turbulence parameters derived from radar and radiosonde was found to agree reasonably well in terms of measures of central tendency. The refractive index structure constant (Cn2) shows a decreasing tendency with height, and it is found to vary as large as 10−14 to as small as 10−19 m−2/3. Range and temporal variation of signal‐to‐noise ratio (SNR) indicated the existence of a stable layer around 8 km height. It is also evident from the present study that the turbulence parameters at this central Himalayan region of complex terrain are higher by 1 order of magnitude than those reported from the southern part of India.

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Estimate of Turbulent Energy Dissipation Rate From the VHF Radar and Radiosonde Observations in the Antarctic

Cited by 34 publications

References 99 publications

Characteristics of Atmospheric Turbulence Retrieved From High Vertical‐Resolution Radiosonde Data in the United States

Characteristics of Atmospheric Turbulence Retrieved From High Vertical‐Resolution Radiosonde Data in the United States

Statistical Analysis of Turbulence Characteristics over the Tropical Western Pacific Based on Radiosonde Data

Estimation of Turbulence Parameters Using ARIES ST Radar and GPS Radiosonde Measurements: First Results From the Central Himalayan Region

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